code: def test_cfp_original(device):
      x = torch.tensor(example_y, device=device).unsqueeze(0)
  
      cfp_layer = Combined_Frequency_Periodicity(
          fr=2,
          fs=44100,
          hop_length=320,
          window_size=2049,
          fc=80,
          tc=0.001,
          g=[0.24, 0.6, 1],
          NumPerOct=48,
      ).to(device)
      X = cfp_layer(x)
      ground_truth = torch.load(
          os.path.join(dir_path, "ground-truths/cfp_original.pt"),
          map_location=device,
      )
  
      for i, j in zip(X, ground_truth):
          assert torch.allclose(
              torch.log(i + episilon),
              torch.log(j + episilon),
              1e-3,
              9e-1,
          )
  
file_path: nnAudio/Installation/tests/test_cfp.py
imports: import pytest
  import librosa
  import torch
  from scipy.signal import chirp, sweep_poly
  import sys
  import os
  from nnAudio.Spectrogram import *
  from parameters import *
  import warnings
label_desc: Use image node_id 1 for calling a global function with example usage: test_cfp_original(device) without return types